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For the planning and implementation of lessons with digital technologies, a subject-specific technology-related professional competence of teachers is of central importance. However, the competency frameworks developed so far remain in a general perspective and do not explicitly address subject-specific issues. Furthermore, digital competencies are predominantly measured with subject-unspecific self-assessment instruments, as subject-specific operationalizations for this area are not yet available in a differentiated form. In this article, the framework for Digital Competencies for Teaching in Science Education (DiKoLAN), a subject-specific framework for pre-service science teachers, is introduced, on the one hand, and, on the other hand, first results of a self-assessment tool based on the framework are described. DiKoLAN defines competency areas highly specific to science, as well as more general competency areas that include aspects common to all subjects. Each competency area is described by competency expectations, which, in turn, are structured with reference to the four technology-related dimensions of the TPACK framework (i.e., Technological and Pedagogical Content Knowledge) and three levels of performance (Name, Describe, Use/Apply). Derived from DiKoLAN, a corresponding self-assessment instrument (DiKoLAN-Grid) was developed and empirically tested for the two competency areas, (n = 118) and Information Search and Evaluation (n = 90), in biology student teachers. By means of path models, tendencies regarding structural correlations of the four components Special Tools (TK), Content-specific Context (TCK), Methods and Digitality (TPK), and Teaching (TPACK) are presented for both competency areas and discussed, as well as in comparison to previously conducted, subject-unspecific surveys.

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Digital technologies have the potential to increase the quality of instruction; however, using digital technologies does not necessarily guarantee high-quality teaching. Therefore, teachers need specific professional knowledge on how to use and implement digital technologies. Moreover, teachers need to know how beliefs about learning with digital technologies impact their teaching. Usually, knowledge and beliefs are assessed via self-report measures and in a subject-unspecific and isolated manner. The present study assesses biology-specific professional knowledge on the use of digital technologies (self-report and performance assessed) and beliefs together. Furthermore, these constructs were related to the quality of lesson plans on honeybees and analysed. Eighty-two biology teacher students from an Austrian university participated in the study. A path model revealed that self-assessed professional knowledge on the use of digital technologies was not a significant predictor of lesson planning quality. In contrast, performance-assessed knowledge and–to some extent–beliefs are significant predictors of the quality of lesson plans with technology integration. Thus, self-report measures on their own do not sufficiently predict the ability to engage in high-quality technology integration in the classroom.

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In order to systematically introduce (prospective) teachers to teaching in the digital world and to lay the foundations for concepts that are meaningful in terms of physics education, essential aspects of learning with and via digital media must be conveyed. In addition to cross-curricular competencies, it is essential to consider subject-specific competencies for the natural sciences since the formation of subject-specific knowledge on the use of digital media in the classroom (TPACK) is the decisive factor for acceptance behaviour and the intention for later use. The questions remain as to what core competencies must be built up by all (prospective) science teachers by the end of their studies and in which sections of university teacher training this should take place. Since no competence frameworks specific to the teaching of science were previously available, nine researchers from eight universities came together to develop a suitable orientation framework. As a result, this contribution presents the structured and graded framework “DiKoLAN – Digitale Kompetenzen für das Lehramt in den Naturwissenschaften [Digital Competencies for Teaching in Science Education]” (see https://dikolan.de).

Using three-dimensional physical models elaborately in their learning, students can develop high-level understanding of models and modeling in science, thereby attaining higher achievement. However, there are in the literature few indications of how teachers should use three-dimensional physical models in instruction and whether teachers’ professional knowledge is a prerequisite for teaching with elaborate use of models. Therefore, our study used a mixed-methods approach to analyze the effects of biology teachers’ domain-specific pedagogical content knowledge (PCK) and content knowledge (CK) on students’ achievement mediated by elaborate model use (ELMO). Our quantitative sample comprised 36 German secondary school teachers whose lessons on the topic of neurobiology were videotaped twice (N = 72 lessons). Teachers completed professional knowledge tests on their PCK and CK. Students’ achievement was measured using pre- and post-knowledge tests. Our qualitative analysis involved five selected teachers according to aspects of ELMO. The results of our study indicated that teachers’ PCK and CK had no direct effect on students’ achievement. However, teachers’ PCK had a significant indirect and positive effect on students’ achievement mediated by ELMO. The findings of our study can provide teachers and researchers examples of how to implement biology instruction with elaborate use of three-dimensional physical models.